---

Precipitation is one of the most intractable elements. The oscillating behavior of the crucial environmental planning (explicit and tacit knowledge of the behavior), is the key variable. Spectrum analysis techniques to understand the behavior of overt or covert methods suitable for the extraction and analysis of climate oscillations with different wave lengths. The size range of the distribution variance across all wave lengths may provide time series. In this study, data from 37 stations Heleh and Mond watershed (both rain and synoptic) from its inception until 2011,  who had over 30 years of data, to analyze the cycle of annual rainfall, interest has been taken. So that the space is 3-2 year cycles in every area of study, the highest annual rainfall events are returned. On this basis, the Story of annual precipitation 95 percent for each of the stations under study and cycle meaningful estimate of the time series of basin data were extracted.

---

Rainfall is one of the most important components of the water cycle and plays a very important role in the measurement of climate characteristic in any area. Limitations such as lack of sufficient information about the amount of rainfall in time and space scale and complexity of the relationship between meteorological elements related to rainfall, causes the calculation of these parameters using the conventional method not to be implemented. One method of evaluating and forecasting of rainfall in each region is time series models. In this research, to predict the average annual rainfall synoptic station at Mahabad, Uromiya and Mako in West Azarbayejan provience during 1984-2013, linear time series ARIMA was used. To investigate model static, Auto Correlation Function (ACF) and Partial Auto Correlation Function (PACF) was applied and with differencing method, the non-static data transformed to static data. In next step, stochastic models to estimate the annual rainfall average were used. With regard to the evaluation criterion such as T, P-VALUE < 0.05 and Bayesian Information Creterion (BIC), ARIMA (1,0,0), ARIMA (0,1,1) and ARIMA (0,1,1) models was determined as a suitable model for predicting annual rainfall in the three selected stations at Uromiya, Makoo and Mahabad. In the following, the annual rainfall for 3 (2013-2016) years is forecasted which based on rainfall data in that time, the adjusted model was acceptable.